• IE interfaces
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• v.23 no.4
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• pp.327-336
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• 2010

We consider a supply chain consisting of a make-to-order manufacturer and N component suppliers and study the impacts of the number of suppliers on component inventory management. The manufacturer has full information and continuously observes the state of both component inventory level and customer backorders. Based on this information, the manufacturer determines whether or not to place a component purchasing order to a supplier among N suppliers even though some orders are in process by other suppliers. The goal of this paper is to numerically identify the manufacturer's purchasing policy which minimizes the total supply chain cost and the best choice of N. Our model contributes to the current literature in that the problem of simultaneously considering multiple outstanding orders and incorporating order setup cost into the model has not been covered yet. From numerical experiment, we investigate how much the policy with N suppliers can contribute to reducing the supply cost compared to the policy with a single supplier.

• The Journal of Information Systems
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• v.14 no.3
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• pp.31-36
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• 2005

Firms seldom survive and prosper solely through their individual efforts. Each firm's performance depends upon the activities and performance of others and hence upon the nature and quality of the direct and indirect relationships a firm develops with its counterparts. Textile companies have tried to improve their organizational competitiveness in order to survive in the digital age global market. The challenge in textile supply chain management is the development of collaboration network which accommodates diverse concerns of various participants while explicitly recognizing interdependencies and promoting effective relationship management. Major contents of the study are as follows. First, ideal collaboration network model from the supply chain of the textile industry is suggested. Second, utilizing the collaboration model, A framework for textile e-marketplaces supply chians is designed to improve customer services and delivery time, to promote information sharing, and shorten product life cycle time. The framework suggested is expected to promote corporate innovation and information sharing, generate infrastructure which provides appropriate communication and operations capabilities for the textile companies.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.27-40
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• 2006

Today's customer demands in supply chains tend to change quickly, variously even in a short time Interval. The uncertainties of customer demands make it difficult for supply chains to achieve efficient inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. Un this paper, we propose an adaptive vendor managed inventory (VMI) model for a two-echelon supply chain with non-stationary customer demands using the action-reward learning method. The Purpose of this model is to decrease the inventory cost adaptively. The control Parameter, a compensation factor, is designed to adaptively change as customer demand pattern changes. A simulation-based experiment was performed to compare the performance of the adaptive VMI model.

• The Journal of Natural Sciences
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• v.5 no.1
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• pp.77-86
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• 1992

By cation-exchange-reaction long-chain organic cationic tensides can be intercalated in the montmorillonite layer space, and thus intercalations-complexes of montmorillonite with different properties of materials can be obtained. Such intercalations-complexes are finding strong technical appliances in many areas and are also used very often as model-systems for studying behaviors of materials. Therefore in this research intercalations-complexes of montmorillonite with organic cationic tensides ad model-systems were synthesized and their behabiors under various different conditions were studied.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.146-158
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• 2004

This paper considers a continuous-review two-echelon inventory control problem with one-to-one replenishment policy incorporated and with lost sales allowed where demand arrives in a stationary Poisson process. The problem is formulated using METRIC-approximation in a combined approach of pricing and (S-l, S) inventory policy, for which a heuristic solution algorithm is derived with respect to the corresponding one-warehouse multi-retailer supply chain. Specifically, decisions on retail pricing and warehouse inventory policies are made in integration to maximize total profit in the supply chain. The objective function of the model consists of sub-functions of revenue and cost (holding cost and penalty cost). To test the effectiveness and efficiency of the proposed algorithm, numerical experiments are performed with two cases. The first case deals with identical retailers and the second case deals with different retailers with different market sizes. The computational results show that the proposed algorithm is efficient and derives quite good decisions.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.49-66
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• 2018

This research explores a value chain structure of VR-AR media including user's perception, uses, and evaluation. The purpose of this research focused on factor analysis and the relationship among user's VR-AR adoption motivations and utilities. This research explores correlation between personal value and using motivation. This study was to identify the value structure of respondent on VR-AR usages based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. This study is based on the analysis of the value chain structure factors that affect VR and AR use behavior (attributes, functional benefits, psychological benefits, use value), 'Hierarchical Value Map' between users' The purpose of the model is to construct a model. For this, 'means-end chain theory' was applied to measure the causal relationship between personal value and VR related use behavior. In order to solve this research problem, 135 people were analyzed through the structured questionnaire using the AR and VR content fitness measure and the second APT laddering, and the use of VR-AR : 1) Functional benefits; 2) Psychological benefits; 3) Means to reach value, 4) Objective value chain structure was identified. The results show that VR users tried to smooth the social life through the new virtual reality audiovisual element, the newness of experience, fun, and pleasure through the departure of reality, vividness of experience, and leading fashion. The AR fitness was a game and a new program, and the value of interacting with other people and the value of 'periwinkle' played an important role through the vividness and peripheral interaction of AR, It was an important choice. The important basic values of users' VR and AR selection were correlated with psychological attributes of interaction with others, achievement, happiness and favorable values.

• Journal of Soil and Groundwater Environment
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• v.10 no.5
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• pp.52-60
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• 2005

The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• Nuclear Engineering and Technology
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• v.25 no.4
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• pp.539-547
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• 1993

A stochastic approach using continuous time Markov process is presented to model the one-dimensional nuclide transport in fractured rock media as a further extension for previous works［1-3］. Nuclide transport of decay chain of arbitrary length in the single planar fractured rock media in the vicinity of the radioactive waste repository is modeled using a continuous time Markov process. While most of analytical solutions for nuclide transport of decay chain deal with the limited length of decay chain, do not consider the case of having rock matrix diffusion, and have very complicated solution form, the present model offers rather a simplified solution in the form of expectance and its variance resulted from a stochastic modeling. As another deterministic way, even numerical models of decay chain transport, in most cases, show very complicated procedure to get the solution and large discrepancy for the exact solution as opposed to the stochastic model developed in this study. To demonstrate the use of the present model and to verify the model by comparing with the deterministic model, a specific illustration was made for the transport of a chain of three member in single fractured rock medium with constant groundwater flow rate in the fracture, which ignores the rock matrix diffusion and shows good capability to model the fractured media around the repository.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.3
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• pp.73-95
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• 2015

Firms have reexamined and restructured their supply chain based on a long-term and partnership perspective as a firm's competitive advantage increasingly relies on its supply chain capability. A number of scholar works has provided evidence to support the positive effects of supply chain collaboration; however, the relationship between collaboration and performance is still inconclusive. This study refuses to have blinded faith on supply chain collaboration, but rather this paper suggests that the contribution of collaboration to supply chain performance improvement can be limited and vary along the contextual characteristics of a buyer-supplier relationship. Moreover, we argue that the relationship between supply chain collaboration and performance can be curvilinear. This paper provides and test hypotheses regarding the relationship between supply chain collaboration and performance. By using data of the Manufacturing Panel Survey (MPS), this study empirically validates the hypotheses. Overall, the results of the study support our hypotheses about a limited contribution of supply chain collaboration to manufacturing performance, which is opposite to a conventional expectation. Particularly, the effects of supply chain collaboration differ depending on the dimensions of performance such as customer satisfaction, quality, cost, delivery, and flexibility as well as the dependency in the buyer-supplier relationship. Moreover, the results of the study indicate that supply chain collaboration and performance may have curvilinear relationships in a certain context. Through a comprehensive model and empirical evidence, this study presents a better understanding of supply chain collaboration and provokes an open discussion about the effects of collaboration. This study also provides insightful implications for managers of buyers as well as suppliers who wish to foster stronger supply chain performance via a deep buyer-supplier relationship and collaboration.